Table of Contents

• Learning Engineering: The Art of Applying Learning Science at ScaleBror Saxberg. 1 [doi]
• Robust Evaluation Matrix: Towards a More Principled Offline Exploration of Instructional PoliciesShayan Doroudi, Vincent Aleven, Emma Brunskill. 3-12 [doi]
• A Visual Approach towards Knowledge Engineering and Understanding How Students Learn in Complex EnvironmentsLauren Fratamico, Sarah Perez, Ido Roll. 13-22 [doi]
• Enabling Real-Time Adaptivity in MOOCs with a Personalized Next-Step Recommendation FrameworkZachary A. Pardos, Steven Tang, Daniel Davis, Christopher Vu Le. 23-32 [doi]
• Learning to Code in Localized Programming LanguagesSayamindu Dasgupta, Benjamin Mako Hill. 33-39 [doi]
• Teaching Students to Recognize and Implement Good Coding StyleEliane S. Wiese, Michael Yen, Antares Chen, Lucas A. Santos, Armando Fox. 41-50 [doi]
• Detecting Diligence with Online Behaviors on Intelligent Tutoring SystemsSteven Dang, Michael Yudelson, Kenneth R. Koedinger. 51-59 [doi]
• Epistemic Cognition: A Promising and Necessary Construct for Enriching Large-scale Online Learning AnalysisPetr Johanes. 61-69 [doi]
• Scaling Expert Feedback: Two Case StudiesDavid A. Joyner. 71-80 [doi]
• Gradescope: A Fast, Flexible, and Fair System for Scalable Assessment of Handwritten WorkArjun Singh, Sergey Karayev, Kevin Gutowski, Pieter Abbeel. 81-88 [doi]
• Writing Reusable Code Feedback at Scale with Mixed-Initiative Program SynthesisAndrew Head, Elena Glassman, Gustavo Soares, Ryo Suzuki, Lucas Figueredo, Loris D'Antoni, Björn Hartmann. 89-98 [doi]
• Creative Learning @ ScaleMitchel Resnick, Karen Brennan, Cristóbal Cobo, Philipp Schmidt. 99-100 [doi]
• Preventing Keystroke Based Identification in Open Data SetsJuho Leinonen, Petri Ihantola, Arto Hellas. 101-109 [doi]
• Do Performance Trends Suggest Wide-spread Collaborative Cheating on Asynchronous Exams?Binglin Chen, Matthew West, Craig B. Zilles. 111-120 [doi]
• Towards Equal Opportunities in MOOCs: Affirmation Reduces Gender & Social-Class Achievement Gaps in ChinaRené F. Kizilcec, Glenn M. Davis, Geoffrey L. Cohen. 121-130 [doi]
• Learning about Learning at Scale: Methodological Challenges and RecommendationsFrans van der Sluis, Tim Van der Zee, Jasper Ginn. 131-140 [doi]
• Discourse: MOOC Discussion Forum Analysis at ScaleAlexander Kindel, Michael Yeomans, Justin Reich, Brandon M. Stewart, Dustin Tingley. 141-142 [doi]
• Demo of Orchestration Graph Engine: Enabling Rich Social Pedagogical Scenarios in MOOCsLouis Faucon, Stian Håklev, Thanasis Hadzilacos, Pierre Dillenbourg. 143-144 [doi]
• Full Engagement Educational Framework: A Practical Experience for a MicroMasterRocael Hernández Rizzardini, Hector R. Amado-Salvatierra. 145-146 [doi]
• CODECAST: An Innovative Technology to Facilitate Teaching and Learning Computer Programming in a C Language Online CourseRémi Sharrock, Ella Hamonic, Mathias Hiron, Sébastien Carlier. 147-148 [doi]
• Taking Informed Action on Student Activity in MOOCsRalf Teusner, Kai-Adrian Rollmann, Jan Renz. 149-152 [doi]
• In-Video Reuse of Discussion Threads in MOOCsQian Zhao, Sashank Varma, Joseph A. Konstan. 153-156 [doi]
• A Crowdsourcing Approach to Collecting Tutorial Videos - Toward Personalized Learning-at-ScaleJacob Whitehill, Margo Seltzer. 157-160 [doi]
• MOOC Dropout Prediction: How to Measure Accuracy?Jacob Whitehill, Kiran Mohan, Daniel T. Seaton, Yigal Rosen, Dustin Tingley. 161-164 [doi]
• Collaboration and Teamwork on a MOOC Platform: A ToolsetThomas Staubitz, Christoph Meinel. 165-168 [doi]
• Incorporating Rich Features into Deep Knowledge TracingLiang Zhang, Xiaolu Xiong, Siyuan Zhao, Anthony Botelho, Neil T. Heffernan. 169-172 [doi]
• Formal Forum Triage: Towards the Strategic Selection of Responses to Student Discussion ForumsNickolas J. G. Falkner, Claudia Szabo, Katrina E. Falkner. 173-176 [doi]
• A Novel Self-Paced Model for Teaching ProgrammingJeff Offutt, Paul Ammann, Kinga Dobolyi, Chris Kauffmann, Jaime Lester, Upsorn Praphamontripong, Huzefa Rangwala, Sanjeev Setia, Pearl Y. Wang, Liz White. 177-180 [doi]
• Google BigQuery for Education: Framework for Parsing and Analyzing edX MOOC DataGlenn Lopez, Daniel T. Seaton, Andrew Ang, Dustin Tingley, Isaac L. Chuang. 181-184 [doi]
• Characterizing ELL Students' Behavior During MOOC Videos Using Content TypeJudith Uchidiuno, Jessica Hammer, Evelyn Yarzebinski, Kenneth R. Koedinger, Amy Ogan. 185-188 [doi]
• A Memory-Augmented Neural Model for Automated GradingSiyuan Zhao, Yaqiong Zhang, Xiaolu Xiong, Anthony Botelho, Neil T. Heffernan. 189-192 [doi]
• One Decision Tree is Enough to Make CustomizationHao Wan, Joseph E. Beck. 193-196 [doi]
• Factor Analysis Reveals Student Thinking using the Mechanics Reasoning InventorySunbok Lee, Zhengzhou Chen, David E. Pritchard, Alex Kimn, Andrew Paul. 197-200 [doi]
• Deep Knowledge Tracing On Programming ExercisesLisa Wang, Angela Sy, Larry Liu, Chris Piech. 201-204 [doi]
• Modeling MOOC Student Behavior With Two-Layer Hidden Markov ModelsChase Geigle, ChengXiang Zhai. 205-208 [doi]
• Getting to Know English Language Learners in MOOCs: Their Motivations, Behaviors, and OutcomesSelen Türkay, Hadas Eidelman, Yigal Rosen, Daniel T. Seaton, Glenn Lopez, Jacob Whitehill. 209-212 [doi]
• Generating Language Activities in Real-Time for English Learners using Language MuseJill Burstein, Nitin Madnani, John Sabatini, Dan McCaffrey, Kietha Biggers, Kelsey Dreier. 213-215 [doi]
• Humans and Machines Together: Improving Characterization of Large Scale Online Discussions through Dynamic Interrelated Post and Thread Categorization (DIPTiC)Yi Cui, Wan Qi Jin, Alyssa Friend Wise. 217-219 [doi]
• CROWDLEARNING: Towards Collaborative Problem-Posing at ScaleAlireza Farasat, Alexander G. Nikolaev, Suzanne Miller, Rahul Gopalsamy. 221-224 [doi]
• What are the Expectations of Disabled Learners when Participating in a MOOC?Francisco Iniesto, Patrick McAndrew, Shailey Minocha, Tim Coughlan. 225-228 [doi]
• Applying and Exploring Bayesian Hypothesis Testing for Large Scale Experimentation in Online Tutoring SystemsVijaya Dommeti, Douglas Selent. 229-232 [doi]
• Designing Adaptive Assessments in MOOCsYigal Rosen, Ilia Rushkin, Andrew Ang, Colin Federicks, Dustin Tingley, Mary Jean Blink. 233-236 [doi]
• Authentic Science Inquiry Learning at Scale Enabled by an Interactive Biology Cloud Experimentation LabZahid Hossain, Engin Bumbacher, Paulo Blikstein, Ingmar H. Riedel-Kruse. 237-240 [doi]
• Intelligent Math Tutor: Problem-Based Approach to Create CognizanceMonika Gupta, Neelamadhav Gantayat, Renuka Sindhgatta. 241-244 [doi]
• D.TRUMP: Data-mining Textual Responses to Uncover Misconception PatternsJoshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk. 245-248 [doi]
• Teamscope: Scalable Team Evaluation via Automated Metric Mining for Communication, Organization, Execution, and EvolutionAn Ju, Elena Glassman, Armando Fox. 249-252 [doi]
• ProjectLens: Supporting Project-based Collaborative Learning on MOOCsHao Fei Cheng, Bowen Yu, Yeong Hoon Park, Haiyi Zhu. 253-256 [doi]
• Data-Driven Feedback Generator for Online Programing CoursesKe Wang, Benjamin Lin, Bjorn Rettig, Paul Pardi, Rishabh Singh. 257-260 [doi]
• Orchestration Graphs: Enabling Rich Social Pedagogical Scenarios in MOOCsStian Håklev, Louis Faucon, Thanasis Hadzilacos, Pierre Dillenbourg. 261-264 [doi]
• Enhancing the Experience Application Program Interface (xAPI) to Improve Domain Competency Modeling for Adaptive InstructionRobert A. Sottilare, Rodney A. Long, Benjamin S. Goldberg. 265-268 [doi]
• A Statistical Framework for Predictive Model Evaluation in MOOCsJosh Gardner, Christopher Brooks. 269-272 [doi]
• Suggesting a Log-Based Creativity Measurement for Online Programming Learning EnvironmentLilach Gal, Arnon Hershkovitz, Andoni Eguíluz Morán, Mariluz Guenaga, Pablo Garaizar. 273-277 [doi]
• Long-Term Peer Reviewing Effort is Anti-ReciprocalYasmine Kotturi, Andrew Du, Scott R. Klemmer, Chinmay Kulkarni. 279-282 [doi]
• The Changing Patterns of MOOC DiscourseNia M. Dowell, Christopher A. Brooks, Vitomir Kovanovic, Srecko Joksimovic, Dragan Gasevic. 283-286 [doi]
• MOOClets: A Framework for Dynamic Experimentation and PersonalizationJoseph Jay Williams, Anna N. Rafferty, Samuel G. Maldonado, Andrew Ang, Dustin Tingley, Juho Kim. 287-290 [doi]
• Criteria for Video Engagement in a Biology MOOCSera Thornton, Ceri Riley, Mary Ellen Wiltrout. 291-294 [doi]
• Pass the Idea Please: The Relationship between Network Position, Direct Engagement, and Course Performance in MOOCsStacey L. Houston II, Katherine A. Brady, Gayathri Narasimham, Douglas H. Fisher. 295-298 [doi]
• Observing Personalizations in Learning: Identifying Heterogeneous Treatment Effects Using Causal TreesBiao Yin, Thanaporn Patikorn, Anthony F. Botelho, Neil T. Heffernan. 299-302 [doi]
• A Probabilistic Approach for Discovering Difficult Course Topics Using Clickstream DataAssma Boughoula, Chase Geigle, ChengXiang Zhai. 303-306 [doi]
• Congruency, Adaptivity, Modularity, and Personalization: Four Experiments in Teaching Introduction to ComputingDavid A. Joyner. 307-310 [doi]
• Mobilizing the Crowd to Create an Open Repository of Research TalksRajan Vaish, Sharad Goel, Amin Saberi. 311-314 [doi]
• Improving Assessment on MOOCs Through Peer Identification and Aligned IncentivesDilrukshi Gamage, Mark E. Whiting, Thejan Rajapakshe, Haritha Thilakarathne, Indika Perera, Shantha Fernando. 315-318 [doi]
• Using Student Annotated Hashtags and Emojis to Collect Nuanced Affective StatesAmy X. Zhang, Michele Igo, Marc Facciotti, David R. Karger. 319-322 [doi]
• A Heuristic Method for Large-Scale Cognitive-Diagnostic Computerized Adaptive TestingJill-Jênn Vie, Fabrice Popineau, Françoise Tort, Benjamin Marteau, Nathalie Denos. 323-326 [doi]
• Comment Ranking Diversification in Forum DiscussionsCurtis G. Northcutt, Kimberly A. Leon, Naichun Chen. 327-330 [doi]
• Access to Massive Open Online Labs through a MOOCWissam Halimi, Christophe Salzmann, Denis Gillet. 331-334 [doi]
• Experimenting Choices of Video and Text Feedback in Authentic Foreign Language Assignments at ScaleXiwen Lu, Xiaolu Xiong, Neil T. Heffernan. 335-338 [doi]